@article{862aa6bfb16a4d90b514eb7998d48682,
title = "Artificial intelligence at the national eye institute",
abstract = "Purpose of reviewThis review highlights the artificial intelligence, machine learning, and deep learning initiatives supported by the National Institutes of Health (NIH) and the National Eye Institute (NEI) and calls attention to activities and goals defined in the NEI Strategic Plan as well as opportunities for future activities and breakthroughs in ophthalmology.Recent findingsOphthalmology is at the forefront of artificial intelligence-based innovations in biomedical research that may lead to improvement in early detection and surveillance of ocular disease, prediction of progression, and improved quality of life. Technological advances have ushered in an era where unprecedented amounts of information can be linked that enable scientific discovery. However, there remains an unmet need to collect, harmonize, and share data in a machine actionable manner. Similarly, there is a need to ensure that efforts promote health and research equity by expanding diversity in the data and workforce.SummaryThe NIH/NEI has supported the development artificial intelligence-based innovations to advance biomedical research. The NIH/NEI has defined activities to achieve these goals in the NIH Strategic Plan for Data Science and the NEI Strategic Plan and have spearheaded initiatives to facilitate research in these areas.",
keywords = "artificial intelligence, bioinformatics, data science, national eye institute, national institutes of health",
author = "Sherif, {Noha A.} and Chew, {Emily Y.} and Chiang, {Michael F.} and Michelle Hribar and James Gao and Goetz, {Kerry E.}",
note = "Funding Information: In addition to funding hypothesis-driven basic and clinical research projects, NEI has also funded innovative, nontraditional vision research making fundamental contributions to the data science and artificial intelligence fields. For example, NEI has co-funded multidisciplinary investigators through a collaborative funding opportunity between NIH and the National Science Foundation (NSF), Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH) (NSF 21–530). The NEI is also an active participant and received funding support on several trans-NIH data science initiatives supported by the NIH Office of Data Science and Strategy. As the area of data science and artificial intelligence continues to grow, we believe that the involvement and support by NEI will also increase in the coming years. Funding Information: Furthermore, the NEI has played an active role supporting the development and growth of small businesses through NEI Small Business Grant Program. This grant provides two funding opportunities: the Small Business Innovation Research (SBIR) program, which funds projects led primarily by a single institution, and the Small Business Technology Transfer program, which funds projects led by small businesses in collaboration with nonprofit institutions. Annually, the NEI invests approximately $24 million in these programs, funding up to 80 grants each year. These grants also provide awardees access to technical assistance programs and expert consultants to support the commercialization process of innovative ocular devices and medications. The advancement of ONL1204 Ophthalmic Solution, a small peptide that delays cell death in patients with retinal detachment until surgical re-attachment can be performed, is one example of work supported by an NEI SBIR grant. Funding Information: The remarkable advances in clinical and computational science and their promise to impact scientific discovery, health equity, and quality of life are energizing. The developments described in this article highlight only a fraction of the innovative developments supported by the NIH in artificial intelligence. NIH programs such as Bridge2AI and AIM-Ahead, and other funded research will address different challenges in the biomedical and vision research field, including more complex artificial intelligence techniques, development of screening and diagnostic devices, clinical decision support, low-vision aids, and innovative treatment applications. The NIH and NEI are committed to continuing to increase the availability of artificial intelligence-ready data, tools, and train the next generation of clinicians and data scientists to seek fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to enhance health, improve quality of life, and reduce illness and disability. Publisher Copyright: {\textcopyright} 2022 Lippincott Williams and Wilkins. All rights reserved.",
year = "2022",
month = nov,
day = "1",
doi = "10.1097/ICU.0000000000000889",
language = "English (US)",
volume = "33",
pages = "579--584",
journal = "Current Opinion in Ophthalmology",
issn = "1040-8738",
publisher = "Lippincott Williams and Wilkins",
number = "6",
}